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𝐒𝐲𝐧𝐭𝐡𝐞𝐭𝐢𝐜 𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐞𝐧𝐭𝐬: 𝐀 𝐖𝐚𝐜𝐤𝐲 𝐖𝐚𝐯𝐢𝐧𝐠 𝐌𝐚𝐧 𝐨𝐟 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡.

Futurelab

To be frank, I think their main user base will be those who do not research customers at the moment. They can help in early-stage idea validation, small hypothesis testing, or stress-testing assumptions before investing in full-scale research.

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WOULD YOU LIKE SOME MORE MONEY?

Futurelab

Every time I speak about the main CX rule Treat others as you want to be treated I have someone scoffing at me for being too idealistic. #NoBullshitCX This Golden Rule literally brings the gold. There are so many misconceptions around it, it makes my blood boil.

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Lesson #4 Revisited: Text Analytics from Machine Learning to LLMs

PeopleMetrics

Example : A restaurant analyzing customer feedback receives these comments: The appetizers were amazing, but the main course was a letdown. The main course was fine, but the dessert was to die for. Whats more, they offer user-friendly interfaces, enabling anyoneregardless of technical skillto unlock their power.

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Even CX champions are struggling to keep up with rising customer expectations – Interview with Adrian McDermott of Zendesk

Adrian Swinscoe

Adrian joins me today to talk about the new Zendesk CX Accelerator report, the main […]. Today’s interview is with Adrian McDermott, Chief Technology Officer at Zendesk. The post Even CX champions are struggling to keep up with rising customer expectations – Interview with Adrian McDermott of Zendesk first appeared on Adrian Swinscoe.

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Discover The Secret of How to Gain Actionable Customer Insights

Beyond Philosophy

One of the main insights Waterton offers is the importance of capturing feedback at the right moment—immediately after the Customer Experience. Our guest, Tim Waterton , Chief Revenue Officer of HappyOrNot ® , brings over 20 years of experience in helping companies gather and analyze customer insights.

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Introduction to Responsible AI: Unpacking the harms

Callminer

The latest in our Responsible AI blog series, the CallMiner Research Lab explores two of the main categories of harms that AI outputs can cause: Harms of Allocation and Harms of Representation.

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Building a resilient system: Our journey to observability at Intercom

Intercom, Inc.

Our main objective was to confirm that traces would make observability workflows more efficient. In the end, we concluded that Honeycomb not only worked better for the main workflow we had identified, but also ticked the boxes on sampling, pricing, and usage metrics – so we avoided the costly vendor migration.